Baseline correction and extraction of heartbeat profiles

ABSTRACT

A device may determine end-of-phase information for a plurality of wavelength channels of photoplethysmography (PPG) data. The device may calculate a set of baseline correction points for each wavelength channel of the plurality of wavelength channels. The set of baseline correction points may be calculated based on end-of-phase information for a wavelength channel of the plurality of wavelength channels and PPG data associated with the wavelength channel. The device may perform a baseline correction for each wavelength channel of the plurality of wavelength channels. A baseline correction may be performed for the wavelength channel based on the set of baseline correction points associated with the wavelength channel and the PPG data associated with the wavelength channel. The device may generate a baseline corrected heartbeat profile using a principal component analysis of a result of baseline correcting each wavelength channel of the plurality of wavelength channels.

RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.16/780,406, filed Feb. 3, 2020, entitled “BASELINE CORRECTION ANDEXTRACTION OF HEARTBEAT PROFILES,” which claims priority to U.S.Provisional Patent Application No. 62/805,170, filed on Feb. 13, 2019,entitled “BASELINE CORRECTION AND EXTRACTION OF HEARTBEAT PROFILES FORFULL SPECTRUM WEARABLE SPECTROMETER,” the contents of which areincorporated herein by reference in their entireties.

BACKGROUND

Photoplethysmography (PPG) is an optical technique that can be used todetect volumetric changes in blood in peripheral circulation (as bloodvolume changes due to the pumping action of the heart). PPG is anon-invasive method that makes measurements at the surface of the skin(e.g., at a fingertip, a wrist, an ear lobe, and/or the like). A PPGdevice may take the form of, for example, a multispectral sensor device(e.g., a binary multispectral (BMS) sensor device) that providesheartbeat time-series data associated with multiple wavelength channels(e.g., 64 wavelength channels). The multispectral sensor device mayinclude multiple sensor elements (e.g., optical sensors, spectralsensors, and/or image sensors), each to receive one of the multiplewavelength channels (via a respective region of a multispectral filter)in order to capture the heartbeat time-series data.

SUMMARY

According to some implementations, a method may include determining, bya device, end-of-phase information for a plurality of wavelengthchannels of PPG data; calculating, by the device, a set of baselinecorrection points for each wavelength channel of the plurality ofwavelength channels, wherein a set of baseline correction points iscalculated based on end-of-phase information for a wavelength channel ofthe plurality of wavelength channels and PPG data associated with thewavelength channel; performing, by the device, a baseline correction foreach wavelength channel of the plurality of wavelength channels, whereina baseline correction is performed for the wavelength channel based onthe set of baseline correction points associated with the wavelengthchannel and the PPG data associated with the wavelength channel; andgenerating, by the device, a baseline corrected heartbeat profile usinga principal component analysis of a result of baseline correcting eachwavelength channel of the plurality of wavelength channels.

According to some implementations, a device may include one or morememories, and one or more processors, communicatively coupled to the oneor more memories, configured to: determine end-of-phase information fora plurality of wavelength channels of PPG data; calculate a set ofbaseline correction points for each wavelength channel of the pluralityof wavelength channels, wherein a set of baseline correction points iscalculated based on end-of-phase information for a wavelength channel ofthe plurality of wavelength channels and PPG data associated with thewavelength channel; perform a baseline correction for each wavelengthchannel of the plurality of wavelength channels, wherein a baselinecorrection is performed for the wavelength channel based on the set ofbaseline correction points associated with the wavelength channel andthe PPG data associated with the wavelength channel; and generate abaseline corrected heartbeat profile using a principal componentanalysis of a result of baseline correcting each wavelength channel ofthe plurality of wavelength channels.

According to some implementations, a non-transitory computer-readablemedium may store one or more instructions. The one or more instructions,when executed by one or more processors of a device, may cause the oneor more processors to: determine end-of-phase information for aplurality of wavelength channels of PPG data; calculate a set ofbaseline correction points for each wavelength channel of the pluralityof wavelength channels, wherein a set of baseline correction points iscalculated based on end-of-phase information for a wavelength channel ofthe plurality of wavelength channels and PPG data associated with thewavelength channel; perform a baseline correction for each wavelengthchannel of the plurality of wavelength channels, wherein a baselinecorrection is performed for the wavelength channel based on the set ofbaseline correction points associated with the wavelength channel andthe PPG data associated with the wavelength channel; and generate abaseline corrected heartbeat profile using a principal componentanalysis of a result of baseline correcting each wavelength channel ofthe plurality of wavelength channels.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A and 1B are diagrams of an example implementation describedherein.

FIG. 2 is a diagram of an example of calculating a set of centerlinecorrection points for a wavelength channel of PPG data.

FIG. 3 is a diagram illustrating improvement provided by usingcenterline baseline correction with exact crossings.

FIGS. 4A and 4B are diagrams illustrating an example of effects of thedifferent baseline correction schemes on an estimation of heartbeatrate.

FIGS. 5A-5C are diagrams illustrating an example of improvement providedby baseline correcting the wavelength channels before applying aprincipal component analysis in association with generating a baselinecorrected heartbeat profile.

FIGS. 6A and 6B are diagrams illustrating an example of asignal-to-noise ratio improvement resulting from compression provided byperforming a principal component analysis of wavelength channels in aspectrum.

FIGS. 7A-7C are diagrams illustrating examples associated with removingredundant crossing points when applying the centerline baselinecorrection scheme.

FIGS. 8A-8D are diagrams illustrating examples associated withidentifying and removing heartbeat cycle outliers.

FIG. 9 is a diagram illustrating an example of an effect of applyingnormalization before generating the baseline corrected heartbeatprofile.

FIG. 10 is a diagram of an example environment in which systems and/ormethods described herein may be implemented.

FIG. 11 is a diagram of example components of one or more devices ofFIG. 10 .

FIG. 12 is a flow chart of an example process for generating a baselinecorrected heartbeat profile, as described herein.

DETAILED DESCRIPTION

The following detailed description of example implementations refers tothe accompanying drawings. The same reference numbers in differentdrawings may identify the same or similar elements. Further, while thefollowing description may use a multispectral sensor device in anexample, the principles, procedures, operations, techniques, and methodsdescribed herein may be used with any other type of sensing device, suchas a spectrometer, an optical sensor, a spectral sensor, and/or thelike.

As described above, a multispectral sensor device may be capable ofmeasuring, obtaining, collecting, or otherwise determining heartbeattime-series data associated with multiple (e.g., 16, 32, 64, and/or thelike) wavelength channels. Such data is herein referred to as PPG data.In practice the PPG data can be quite noisy, and can include a slopingbaseline (e.g., ascending, descending, or both) and/or a baseline shiftthat obscures the signal. Due to such noise and/or baseline issues,segmenting the PPG data into systolic phases (e.g., times during whichthe heart is contracting) and diastolic phases (e.g., times during whichthe heart is resting) can be difficult. Thus, it is often difficult touse the PPG data in association with performing a biometric monitoringaction because the raw PPG data may lead to inaccurate, unreliableresults.

In some cases, PPG data can be processed in order to determine heartbeatcycle data that identifies start and end times of heartbeat cycles. Itis then possible to perform a biometric monitoring action based on thisheartbeat cycle data. However, sloping baselines and/or baseline shiftsmay still be present in the heartbeat cycle data, which can negativelyimpact accuracy and/or reliability associated with the biometricmonitoring action.

Some implementations described herein provide a device capable ofgenerating a baseline corrected heartbeat profile. The baselinecorrected heartbeat profile is a heartbeat profile for which slopingbaselines and/or baseline shifts have been at least partially corrected(e.g., so as to reduce or eliminate an impact of the sloping baselinesand/or baseline shifts on the heartbeat profile). In someimplementations, the baseline corrected heartbeat profile can begenerated based on a plurality of wavelength channels of PPG data (e.g.,64 channels of PPG data). In some implementations, a baseline correctionmay be performed for each of the plurality of wavelength channels, afterwhich a baseline corrected heartbeat profile can be generated using aprincipal component analysis. Additional details regarding generation ofthe baseline corrected heartbeat profile are described below.

In some implementations, the baseline corrected heartbeat profile can beused in association with performing a biometric monitoring action, suchas vital sign monitoring (e.g., instantaneous heart rate determination,blood pressure determination, and/or the like), or another type ofbiometric determination and/or monitoring (e.g., blood oxygenationdetermination, augmentation index determination, hydrationdetermination, and/or the like). Here, performing the biometricmonitoring action using the baseline corrected heartbeat profile mayimprove accuracy and/or reliability of a result of the biometricmonitoring action (e.g., as compared to using raw PPG data or ascompared to using heartbeat cycle data that has not been baselinecorrected).

FIGS. 1A and 1B are diagrams of an example implementation 100 describedherein.

As shown in FIG. 1A, a multispectral sensor device may be positionedrelative to a skin surface of a subject. For example, as shown in FIG.1A, the multispectral sensor device may be a device worn on the wrist ofthe subject. In some implementations, the multispectral sensor devicemay be positioned relative to the skin surface at another location onthe body, such as on a fingertip, an arm, a leg, an ear lobe, and/or thelike. In some implementations, the multispectral sensor device includesa BMS sensing device that operates in, for example, the visible (VIS)spectrum, the near infrared (NIR) spectrum, and/or the like.

As shown by reference 105, the multispectral sensor device may determine(e.g., measure, gather, collect, and/or the like) PPG data (e.g., rawheartbeat data) associated with N (N>1) wavelength channels. The PPGdata includes, for each of the N wavelength channels, photometricresponse data that indicates a blood volume beneath the skin surface atthe location of the multispectral sensor device at a given time point.

As shown by reference number 110, a heartbeat cycle data device mayobtain the PPG data from the multispectral sensor device. The heartbeatcycle data device is a device capable of generating a baseline correctedheartbeat profile, as described herein. In some implementations, theheartbeat cycle data device may be integrated with the multispectralsensor device (e.g., in a same package, a same housing, on a same chip,and/or the like). Alternatively, the heartbeat cycle data device may beseparate (e.g., remotely located) from the multispectral sensor device.

In some implementations, the heartbeat cycle data device may obtain thePPG data in real-time or near real-time (e.g., when the multispectralsensor device is configured to provide the PPG data as the multispectralsensor device obtains the PPG data). Additionally, or alternatively, theheartbeat cycle data device may obtain the PPG data based on themultispectral sensor device (e.g., automatically) providing the PPG dataon a periodic basis (e.g., every one second, every five seconds, and/orthe like). Additionally, or alternatively, the heartbeat cycle datadevice may obtain the PPG data from the multispectral sensor devicebased on requesting the PPG data from the multispectral sensor device.

As shown by reference number 115, the heartbeat cycle data device maydetermine end-of-phase information for the N wavelength channels of thePPG data. In some implementations, the end-of-phase information mayinclude, for each of the N wavelength channels, information thatidentifies end points of positive phases in the PPG data (hereinreferred to as ends-of-positive phases (EoPPs) and/or information thatidentifies end points of negative phases in the PPG data (hereinreferred to as ends-of-negative phases (EoNPs)). A positive phase(indicating the systolic phase of a heartbeat) in the PPG data and anadjacent negative phase (indicating the diastolic phase of theheartbeat) defines one heartbeat cycle period. Therefore, start and endtimes of heartbeat cycles can be defined by EoNPs and EoPPs in the PPGdata.

In some implementations, the heartbeat cycle data device may determinethe end-of-phase information by determining heartbeat cycle data basedon the PPG data. For example, in some implementations, the heartbeatcycle data device may determine heartbeat cycle data that identifiesstart and end points of heartbeat cycles indicated by the PPG data and,therefore, may determine EoNPs and EoPPs for each wavelength channel inthe PPG data. In some implementations, the heartbeat cycle data devicemay use feature vectors based on moving slopes to determine the EoPPsand EoNPs in the PPG data for each wavelength channel. In someimplementations, the heartbeat cycle data device may determine theheartbeat cycle data in a manner described in U.S. patent applicationSer. No. 16/210,740, filed on Dec. 8, 2018, and entitled “AUTONOMOUSFULL SPECTRUM BIOMETRIC MONITORING,” the content of which isincorporated by reference herein in its entirety.

As shown by reference 120, the heartbeat cycle data device may calculatea set of baseline correction points for each of the N wavelengthchannels. A set of baseline correction points, associated with a givenwavelength channel, includes a set of points that define a baseline ofthe PPG data for the given wavelength channel. In some implementations,the heartbeat cycle data device may calculate the set of baselinecorrection points for a given wavelength channel based on end-of-phaseinformation (e.g., EoNPs and/or EoPPs) for the given wavelength channeland PPG data associated with the given wavelength channel.

In some implementations, for a given wavelength channel, the set ofbaseline correction points may be a set of trough points (e.g., truetrough points) of the given wavelength channel. In such a case, theheartbeat cycle data device may calculate the set of baseline correctionpoints based on end-of-phase information that identifies EoNPsassociated with the given wavelength channel. In some implementations,the heartbeat cycle data device may derive the set of trough points fora given wavelength channel based on searching for minima points betweenEoNP timesteps versus wFV time steps prior to the EoNP time steps. Here,wFV is a window width of a feature vector based on which the heartbeatcycle data is determined. That is, in some implementations, the set oftrough points for a given wavelength channel may be determined based onmoving slopes transformed data, where wFV is a setting associated withthe transformation. In some implementations, the heartbeat cycle datadevice may perform baseline correction using only the set of troughpoints, as described below.

Alternatively, in some implementations, for a given wavelength channel,the set of baseline correction points may be a set of peak points (e.g.,true peak points) of the given wavelength channel. In such a case, theheartbeat cycle data device may calculate the set of baseline correctionpoints based on end-of-phase information that identifies EoPPsassociated with the given wavelength channel. In some implementations,the heartbeat cycle data device may derive the set of peak points for agiven wavelength channel based on searching for maxima points betweenEoPP timesteps versus wFV time steps prior to the EoPP time steps. Insome implementations, the heartbeat cycle data device may performbaseline correction using only the set of peak points, as describedbelow. That is, in some implementations, the set of peak points for agiven wavelength channel may be determined based on moving slopestransformed data, where wFV is a setting associated with thetransformation.

Alternatively, in some implementations, for a given wavelength channel,the set of baseline correction points may be a set of centerline pointsfor the given wavelength channel. In such a case, the heartbeat cycledata device may calculate the set of baseline correction points based onend-of-phase information that identifies EoPPs associated with the givenwavelength channel and information that identifies EoNPs associated withthe given wavelength channel. In some implementations, the heartbeatcycle data device may determine the set of centerline points for thegiven wavelength channel based on a set of trough points (e.g., derivedbased on the EoNPs associated with the given wavelength channel) and aset of peak points (e.g., derived based on the EoPPs associated with thegiven wavelength channel). An example of calculating a set of centerlinepoints is provided below with regard to FIG. 2 . In someimplementations, the heartbeat cycle data device may perform baselinecorrection using only the centerline points, as described below.

As shown by reference 125, the heartbeat cycle data device may perform abaseline correction for each of the N wavelength channels. In someimplementations, the heartbeat cycle data device may perform a baselinecorrection for a given wavelength channel based on the set of baselinecorrection points (e.g., the set of trough points, the set of peakpoints, or the set of centerline points) associated with the givenwavelength channel and the PPG data associated with the given wavelengthchannel. In some implementations, the heartbeat cycle data device mayperform the baseline correction based on subtracting a baseline, definedby the set of baseline correction points, from the PPG data curve. Forexample, for a given wavelength channel, the heartbeat cycle data devicemay form a baseline by connecting the set of baseline correction points(e.g., the set of trough points, the set of peak points, or the set ofcenterline points). Next, the heartbeat cycle data device may subtractthe baseline from the PPG data curve, thereby baseline correcting thePPG data. In some implementations, the heartbeat cycle data device mayperform such a baseline correction for each of the N wavelengthchannels.

As shown by reference 130, the heartbeat cycle data device may generatea baseline corrected heartbeat profile based on a result of baselinecorrecting each of the N wavelength channels. In some implementations,the heartbeat cycle data device may generate the baseline correctedheartbeat profile based on performing a principal component analysis(PCA) of the N baseline corrected wavelength channels. For example,results of baseline correcting the N wavelength channels can be providedas input to a PCA algorithm, and the PCA algorithm may provide, as anoutput, a first principal component (PC1) result. Here, the PC1 resultmay be univariate time series data (i.e., single channel data) thatdefines a baseline corrected heartbeat profile. The PCA acts to compressthe multi-channel PPG data into univariate time series data (in the formof PC1). Notably, PC1 has a higher signal-to-noise ratio (SNR) than SNRsof individual wavelength channels and, therefore, may enable improvedbiometric monitoring, as illustrated below by FIGS. 6A and 6B.

In some implementations, the heartbeat cycle data device may perform abaseline correction of the baseline corrected heartbeat profile. Forexample, a baseline shift may result from compression to PC1 by the PCAwhen the heartbeat cycle data performs baseline correction using sets oftrough points for each of the N wavelength channels or when theheartbeat cycle data device performs baseline correction using sets ofpeak points for each of the N wavelength channels. Thus, furtherimprovement may be provided by performing a baseline correction of thebaseline corrected heartbeat profile. Here, the heartbeat cycle datadevice may calculate a set of baseline correction points for thebaseline corrected heartbeat profile, and may perform, using the set ofbaseline correction points for the baseline corrected heartbeat profile,a baseline correction for the baseline corrected heartbeat profile. Thedetermination of a set of correction points for the baseline correctedheartbeat profile and the subsequent baseline correction of the baselinecorrected heartbeat profile may be performed in a similar manner asdescribed above.

In some implementations, performing the baseline correction on thebaseline corrected heartbeat profile may provide additional accuracyand/or reliability of a biometric monitoring action by reducing oreliminating the baseline shift resulting from the compression to PC1provided by the PCA. In some implementations, one or more additionalbaseline corrections may be performed in order to further improveaccuracy and/or reliability of a subsequently performed biometricmonitoring action. Notably, when the heartbeat cycle data performsbaseline correction using sets of centerline points for each of the Nwavelength channels, there may be no need to perform the baselinecorrection of the baseline corrected heartbeat profile data (e.g., dueto a characteristic of PCA that applies mean centering, which isequivalent to centerline baseline correction).

In some implementations, as shown by reference number 135, the heartbeatcycle data device may provide the baseline corrected heartbeat profileand/or information associated with the baseline corrected heartbeatprofile. For example, in some implementations, the heartbeat cycle datadevice may provide the baseline corrected heartbeat profile to a deviceconfigured to perform vital sign monitoring (e.g., instantaneous heartrate determination, blood pressure determination, and/or the like). Asanother example, in some implementations, the heartbeat cycle datadevice may provide the baseline corrected heartbeat profile to a deviceconfigured to perform another type of biometric monitoring (e.g., bloodoxygen saturation determination, hydration determination, and/or thelike). In some implementations, the heartbeat cycle data device maydetermine an instantaneous heart rate based on the baseline correctedheartbeat profile, and may provide (e.g., for display via a displayscreen of the multispectral sensor device and/or the heartbeat cycledata device) information that identifies the instantaneous heart rate.

In this way, a heartbeat cycle data device can generate a baselinecorrected heartbeat profile that permits a biometric monitoring actionto be performed with increased accuracy and/or increased reliability(e.g., as compared to performing the biometric monitoring action basedon raw PPG data, or as compared to performing the biometric monitoringaction based on heartbeat cycle data that has not been baselinecorrected).

As indicated above, FIGS. 1A and 1B are provided merely as examples.Other examples may differ from what is described with regard to FIGS. 1Aand 1B.

FIG. 2 is a diagram of an example of calculating a set of centerlinecorrection points for a wavelength channel of PPG data. In someimplementations, as indicated in FIG. 2 , a set of centerline points maybe a set of points that define a baseline that is approximately midwaybetween a baseline defined by a set of trough points for the wavelengthchannel and a baseline defined by a set of peak points for thewavelength channel.

In some implementations, the heartbeat cycle data may determine the setof centerline points as follows. The heartbeat cycle data device maydetermine a set of trough points for the wavelength channel (e.g., inthe manner described above), and determine a trough baseline based onthe set of trough points. In FIG. 2 , the set of trough points areidentified as points T1 through T4, and the solid lines connectingpoints T1 through T4 form the trough baseline. The heartbeat cycle datamay also determine a set of peak points for the wavelength channel(e.g., in the manner described above), and determine a peak baselinebased on the set of peak points. In FIG. 2 , the set of peak points areidentified as points P1 through P3, and the dashed lines connectingpoints P1 through P3 form the peak baseline.

Next, the heartbeat cycle data device may derive peak intersectionpoints, which can be identified as a set of points at which the peakbaseline is intersected by lines (e.g., a vertical lines) emanating fromthe trough points. An example of such a peak intersection point islabeled as point TP2 in FIG. 2 . Similarly, the heartbeat cycle datadevice may derive trough intersection points, which can be identified asa set of points at which the trough baseline is intersected by lines(e.g., vertical lines) emanating from the peak points. An example ofsuch a trough intersection point is labeled as point PT2 in FIG. 2 .

Next, the heartbeat cycle data device may determine mid-points on thelines between the peak intersection points and the associated troughpoints. An example of a mid-point on the line between peak intersectionpoint TP2 and trough point T2 is labeled as TPm2 in FIG. 2 . Similarly,the heartbeat cycle data device may determine mid-points on the linesbetween the trough intersection points and the associated peak points.An example of a mid-point on the line between trough intersection pointPT2 and peak point P2 is labeled as PTm2 in FIG. 2 . While not labeledin FIG. 2 , other mid-points can be determined in a similar manner.

Next, the heartbeat cycle data device may form a centerline baseline byconnecting the mid-points on the lines between the peak intersectionpoints and the associated trough points, and the mid-points on the linesbetween the trough intersection points and the associated peak points.For example, as indicated in FIG. 2 , the heartbeat cycle data devicemay connect point TPm2 to point PTm2, as well as other determinedmid-points (not labeled in FIG. 2 ), to form the indicated centerlinebaseline.

Next, the heartbeat cycle data device may identify intersection pointsof the centerline baseline with the PPG data curve. An example of suchan intersection is labeled as point X2 in FIG. 2 . In someimplementations, the intersection points of the centerline baseline withthe PPG data curve may be used to identify the set of centerlinecorrection points for the wavelength channel. For example, for a givenintersection point, the heartbeat cycle data may identify a PPG datapoint nearest to the given intersection point, and this nearest PPG datapoint may be used as one of the set of centerline correction points.Thus, in some implementations, the set of centerline correction pointsfor the given wavelength channel may include a set of PPG data pointsnearest to crossing points of the determined centerline. As anotherexample, for a given intersection point, the heartbeat cycle data devicemay determine (e.g., using linear interpolation) an interpolated PPGdata point corresponding to an exact crossing point of the centerlinebaseline and the PPG data curve, and this interpolated PPG data pointmay be used as one of the set of centerline correction points. Thus, insome implementations, the set of centerline correction points for thegiven wavelength channel may include a set of exact crossing points(i.e., a set of interpolated PPG data points). In some implementations,the heartbeat cycle data device may perform this process for each of theN wavelength channels.

In some implementations, the set of centerline correction points mayinclude one or more nearest PPG data points and one or more exactcrossing points. For example, the heartbeat cycle data device may use anearest PPG data point when the distance from the intersection point tothe nearest PPG data point is less than or equal to a threshold value,and may use an interpolated PPG data point when the distance from theintersection point to the nearest data point is greater than thethreshold value.

As indicated above, FIG. 2 is are provided merely as an example. Otherexamples may differ from what is described with regard to FIG. 2 .

In some implementations, use of one or more exact crossing points todetermine the start and end points of each heartbeat cycle may providefurther improvement to the baseline corrected heartbeat profile. FIG. 3is a diagram illustrating improvement provided by using centerlinebaseline correction with exact crossings. In FIG. 3 , linescorresponding to heartbeat cycles, associated with a centerline baselinecorrected heartbeat profile, are overlaid to show starting points andending points relative to the centerline baseline. Here, the centerlinebaseline is represented as a horizontal line at a value of 0. Notably,identification of individual heartbeat cycles is not necessary forunderstanding the concept illustrated by FIG. 3 ; consequently, cleardelineation of each heartbeat cycle is not shown.

In the left diagram of FIG. 3 , centerline baseline correction wasperformed without using exact crossings for determining the set ofcenterline points. Rather, the set of centerline points was determinedusing PPG data points nearest to intersections of a centerline with thePPG data curve (rather than using linear interpolation to determineexact crossing points). In the right diagram of FIG. 3 , centerlinebaseline correction was performed using exact crossings for determiningthe set of centerline points. That is, the set of centerline points wasdetermined using linear interpolation to determine exact crossing pointsof the centerline with the PPG data curve.

As indicated by comparing the left diagram and the right diagram in FIG.3 , the use of exact crossings for determining the set of centerlinepoints reduces a standard deviation in a fluctuation of the start andend points of heartbeat cycles of the heartbeat profile relative to thecenterline baseline. For example, start and end points of the heartbeatcycles shown in the left diagram of FIG. 3 fluctuate from the baselinein a wide range (e.g., from approximately 0.00 to approximately 0.025for start points, and from approximately 0.00 to approximately −0.025for end points), while start and end points of the heartbeat cyclesshown in the right diagram of FIG. 3 do not fluctuate from the baseline(e.g., are equal to 0.00). Here, use of the heartbeat profile defined bythe heartbeat cycles in the right diagram of FIG. 3 (i.e., the heartbeatprofile that uses exact crossings for centerline baseline correction)provides improved accuracy and/or reliability for biometric monitoringdue to this lack of fluctuation of start and end points of the heartbeatcycles relative to the centerline baseline.

As indicated above, FIG. 3 is provided merely as an example. Otherexamples may differ from what is described with regard to FIG. 3 .

In some implementations, the baseline correction schemes describedabove—trough, peak, and centerline—serve the purposes of baselinecorrection and identifying a robust start and end time of each heartbeatcycle such that an extracted heartbeat profile will be relativelyconsistent and/or will not be significantly affected by environmentalfactors. FIGS. 4A and 4B are diagrams illustrating an example of effectsof the different baseline correction schemes on an estimation ofheartbeat rate. More specifically, FIG. 4A is a diagram illustrating anexample of the effects of the baseline correction schemes oninstantaneous heartbeat rate estimation, while FIG. 4B is a diagramillustrating an example of the effects of the baseline correctionschemes on mean and standard deviation of a heartbeat rate estimation.

As illustrated in FIGS. 4A and 4B, the centerline baseline correctionscheme may, in some cases, deliver a more consistent heartbeat rateestimation than the trough baseline correction scheme and the peakbaseline correction scheme. This can be due to the fact that mosttypical heartbeat cycles show a relatively sharp anacrotic phase (i.e.,ascending phase) followed by a relatively slower catacrotic phase (i.e.,descending phase). In some implementations, the centerline baselinecorrection scheme captures these sharp inflection points duringascending phases and, hence, may deliver more precise segmentation ofheartbeat cycles.

However, in some cases, use of the trough baseline correction scheme orthe peak baseline correction scheme may be advantageous becauseimplementation of the trough or peak baseline correction schemes may befaster and/or require less computing power than implementation of thecenterline baseline correction scheme (while still providing anacceptable level of accuracy and/or reliability).

As indicated above, FIGS. 4A and 4B are provided merely as examples.Other examples may differ from what is described with regard to FIGS. 4Aand 4B.

As described above, in some implementations, the heartbeat cycle datadevice may perform baseline correction for a given wavelength channel ofPPG data, and may then generate a baseline corrected heartbeat profilefrom the baseline corrected wavelength channels using a PCA. That is, insome implementations, the heartbeat cycle data device may apply abaseline correction scheme on individual wavelength channels prior toapplying a PCA to the wavelength channels (e.g., for data compressioninto PC1). In some implementations, baseline correcting the wavelengthchannels before applying the PCA to the baseline corrected wavelengthchannels in this manner reduces baseline shift.

FIGS. 5A-5C are diagrams illustrating an example of improvement providedby baseline correcting the N wavelength channels before applying the PCAin association with generating the baseline corrected heartbeat profile.Notably, identification of individual signals is not necessary forunderstanding the implementation illustrated by FIGS. 5A-5C;consequently, clear delineation of each signal is not shown.

FIG. 5A is a diagram illustrating an example of a heartbeat profile thatresults when no baseline correction is performed and no PCA isperformed. FIG. 5B is a diagram illustrating an example of a heartbeatprofile that results when no baseline correction is performed and PCA isapplied. FIG. 5C is a diagram illustrating an example of a heartbeatprofile that results when baseline correction is performed, after whichPCA is applied (e.g., as described in association with FIGS. 1A and 1B).In FIG. 5C, centerline baseline correction was performed on thewavelength channels. As is illustrated when comparing FIGS. 5A, 5B, and5C, performing baseline correction and then performing PCA provides thebest performance of these three options in terms of identifyingrelatively consistent heartbeat profiles.

As indicated above, FIGS. 5A-5C are provided merely as examples. Otherexamples may differ from what is described with regard to FIGS. 5A-5C.

As described above, PPG data may be collected for N wavelength channelsacross a full spectrum (e.g., an MR spectrum) in association withgenerating a baseline corrected heartbeat profile. One advantage ofusing PPG data across the full spectrum (rather than PPG data from asingle wavelength channel in the spectrum) is improved SNR. FIGS. 6A and6B are diagrams illustrating an example of an SNR improvement resultingfrom compression provided by performing a PCA on wavelength channels ina spectrum.

FIG. 6A shows two example heartbeat cycles collected by 64 individualchannels (e.g., with wavelengths from 780 nanometers (nm) to 1062 nm).These lines are labeled with markers in FIG. 6A. Notably, identificationof the individual wavelength channels is not necessary for understandingthe implementation illustrated by FIG. 6A; consequently, cleardelineation of each wavelength channel is not shown. FIG. 6A furtherillustrates (in a line without markers) the two example heartbeat cyclesas determined based on full spectrum PPG data and using PCA compression.As can be clearly seen in FIG. 6A, the SNR in the PC1 signal issignificantly higher than a SNR of any individual wavelength channel. Inthis example, the signal strength of PC1 may be relatively close to atheoretical value of 8 (e.g., sqrt(64)=8) times greater than that of theindividual wavelength channels.

FIG. 6B shows a comparison of heartbeat cycles determined from a singlechannel (shown in the left portion of FIG. 6B) and heartbeat cyclesdetermined from a PC1 based on multiple wavelength channels (shown inthe right portion of FIG. 6B). Notably, identification of the individualheartbeat cycles is not necessary for understanding the implementationillustrated by FIG. 6B; consequently, clear delineation of eachheartbeat cycle is not shown. As indicated by comparing the left andright portions of FIG. 6B, the heartbeat cycles determined from PCIinclude comparatively less noise than those determined from theindividual wavelength channel.

As indicated above, FIGS. 6A and 6B are provided merely as examples.Other examples may differ from what is described with regard to FIGS. 6Aand 6B.

As described above, in some implementations, the heartbeat cycle datadevice may use centerline baseline correction, whereby the heartbeatcycle data device uses a set of centerline points for performingbaseline correction. In some cases, when dealing with relatively noisyPPG data and applying centerline correction, there may be one or moreinstances when a PPG response in a descending phase does not always godown monotonically or, less commonly, one or more instances when a PPGresponse in an ascending phase does not go up monotonically. Suchinstances can result in over-divided heartbeat cycles that reduceaccuracy and/or reliability of a determined heartbeat profile.Therefore, in some cases, the heartbeat cycle data device may beconfigured to remove these problematic instances that cause over-dividedheartbeat cycles.

FIGS. 7A-7C are diagrams illustrating examples associated with removingredundant crossing points when applying the centerline baselinecorrection scheme. The left portion of FIG. 7A is a diagram depicting anexample of an instance of a PPG response in an individual wavelengthchannel that can cause an over-divided heartbeat cycle (herein referredto as a redundant crossing), while the right portion of FIG. 7A is adiagram depicting an example of an instance of a PPG response in PC1 ofmultiple wavelength channels that can cause an over-divided heartbeatcycle. Notably, identification of the individual wavelength channels isnot necessary for understanding the concept illustrated by FIG. 7A;consequently, clear delineation of each wavelength channel is not shown.

In some implementations, the heartbeat cycle data device may beconfigured to remove these problematic redundant crossings. For example,in some implementations, when determining the set of centerline pointsfor a given wavelength channel, the heartbeat cycle data device mayremove all negative-to-positive crossings between a peak point, of theset of peak points, and a subsequent trough point of the set of troughpoints (i.e., a descending phase), and may also remove all but a lastnegative-to-positive crossing between a trough point, of the set oftrough points, and a subsequent peak point of the set of peak points(i.e., an ascending phase).

In some implementations, a baseline corrected heartbeat data profilegenerated after removal of the redundant crossings may be improved(e.g., may have a higher SNR). FIG. 7B illustrates an effect of removingthe redundant crossings in the manner described above. The left andmiddle diagrams of FIG. 7B illustrate heartbeat cycles provided usingindividual wavelength channels and PC1, respectively, withoutimplementation of the above described approach for removing redundantcrossings, while the right diagram of FIG. 7B illustrates heartbeatcycles provided using PC1 results with implementation of the abovedescribed approach for removing redundant crossings. Notably,identification of the individual heartbeat cycles is not necessary forunderstanding the implementation illustrated by FIG. 7B; consequently,clear delineation of each heartbeat cycle is not shown.

As indicated by comparing the left and middle diagrams in FIG. 7B, PCAmay provide removal of some redundant crossings that cause over-dividedheartbeat cycles, even without implementation of the above describedapproach for removal of redundant crossings. However, implementation ofthe above described approach for removing redundant crossing on PC1responses can further reduce redundant crossings that cause over-dividedheartbeat cycles, as indicated by comparing the middle and rightdiagrams. FIG. 7C illustrates these effects in terms of a histogram ofheartbeat cycle period lengths. The left, middle, and right portions ofFIG. 7C correspond to the left, middle, and right portions of FIG. 7B,respectively. As can be seen in FIG. 7C, applying the above describedapproach for removal of redundant crossings results in a Gaussian-likedistribution that is not significantly biased by redundant crossings.

As indicated above, FIGS. 7A-7C are provided merely as examples. Otherexamples may differ from what is described with regard to FIGS. 7A-7C.

In some implementations, when dealing with PPG data with an unstablebaseline, there may be cases in which heartbeat cycles in a region of achanging baseline may be suppressed. As a result, a determined heartbeatprofile in that region may have merged heartbeat cycles (and anover-sized period). In some implementations, a screening of heartbeatcycles with periods that deviate from a popular heartbeat cycle periodby a threshold amount can be used to remove such outliers. FIGS. 8A-8Dare diagrams illustrating examples associated with identifying andremoving such heartbeat cycle outliers.

FIG. 8A illustrates an example of PPG responses of a set of wavelengthchannels prior to baseline correction, and FIG. 8B illustrates anexample of PPG responses of the set of wavelength channels and a PC1resulting after applying baseline correction (e.g., using centerlinebaseline correction). Notably, identification of the individual signalsis not necessary for understanding the implementation illustrated byFIGS. 8A and 8B; consequently, clear delineation of each signal is notshown. The rectangular regions in FIGS. 8A and 8B indicate heartbeatcycles that are suppressed due to an unstable baseline, which causes theheartbeat cycles in those regions to have merged. To address such anissue, the heartbeat cycle data device may be configured to screenheartbeat cycles that have periods that differ from a particular periodby a threshold amount. That is, in some implementations, the heartbeatcycle data device may identify a heartbeat cycle as a heartbeat cycleoutlier, and may remove the heartbeat cycle outlier prior to generatingthe baseline corrected heartbeat profile. In some implementations, theheartbeat cycle data device may identify the heartbeat cycle as aheartbeat cycle outlier based on determining that a period of theheartbeat cycle differs from a popular heartbeat cycle period by anamount that satisfies a threshold. For example, the heartbeat cycle datadevice may be configured to identify heartbeat cycles with periods thatdiffer from a popular heartbeat cycle period by at least two times astandard deviation of the popular heartbeat cycle period. In someimplementations, the popular heartbeat cycle period may be defined as amost frequently occurring heartbeat cycle period (i.e., a mode heartbeatcycle period), an average heartbeat cycle period, a weighted averageheartbeat cycle period, or using another statistical measure.

FIGS. 8C and 8D are diagrams illustrating an example of the effect ofremoving heartbeat cycle outliers for both a single channel scenario anda PC1 scenario. Notably, identification of the individual heartbeatcycles is not necessary for understanding the concept illustrated byFIGS. 8C and 8D; consequently, clear delineation of each heartbeat cycleis not shown. As can be seen based on comparing FIGS. 8C and 8D, PC1combined with removal of heartbeat cycle outliers in the mannerdescribed above provides an improved signal (e.g., as compared to singlechannel without outlier removal, PC1 without outlier removal, and singlechannel with outlier removal).

In some implementations, the heartbeat cycle data device may beconfigured to remove heartbeat cycle outliers in another manner. Forexample, the heartbeat cycle data device may be configured to removeheartbeat cycle outliers using a chemometric outlier removal method,such as Mahalanobis Distance, Q-residuals, Hotelling's T-Square, MedianAbsolute Deviation (MAD), a single class support vector machine (SVM),and/or the like.

As indicated above, FIGS. 8A-8D are provided merely as examples. Otherexamples may differ from what is described with regard to FIGS. 8A-8D.

In some implementations, the heartbeat cycle data device may beconfigured to normalize a result of baseline correcting each of the Nwavelength channels prior to generating the baseline corrected heartbeatprofile using PCA. Normalization in which spectra are divided by areasunder their curves to remove an effect of varying photometric responsesincurred during sampling. FIG. 9 is a diagram illustrating an example ofan effect of applying normalization before generating the baselinecorrected heartbeat profile. As can be seen based on comparing the leftand right portions of FIG. 9 , normalization can be effective inreducing variations occurring during sampling, which results in animproved PC1 result.

As indicated above, FIG. 9 is provided merely as an example. Otherexamples may differ from what is described with regard to FIG. 9 .

FIG. 10 is a diagram of an example environment 1000 in which systemsand/or methods described herein may be implemented. As shown in FIG. 10, environment 1000 may include a multispectral sensor device 1005, aheartbeat cycle data device 1010, and a network 1015. Devices ofenvironment 1000 may interconnect via wired connections, wirelessconnections, or a combination of wired and wireless connections.

Multispectral sensor device 1005 includes a device capable of measuring,gathering, collecting, or otherwise determining PPG data associated witha plurality of wavelength channels, as described herein. For example,multispectral sensor device 1005 may include a multispectral sensingdevice capable of determining PPG data (in the form of multivariatetime-series data) on each of 64 wavelength channels. In someimplementations, multispectral sensor device 1005 may operate in thevisible spectrum, the near infrared spectrum, the infrared spectrum,and/or the like. In some implementations, multispectral sensor device1005 may be a wearable device (e.g., a device worn that can be worn on awrist, a finger, an arm, a leg, a head, an ear, and/or the like). Insome implementations, multispectral sensor device 1005 may be integratedwith heartbeat cycle data device 1010 (e.g., such that multispectralsensor device 1005 and heartbeat cycle data device 1010 are on the samechip, in the same package, in the same housing, and/or the like).Alternatively, in some implementations, multispectral sensor device 1005may be separate from heartbeat cycle data device 1010. In someimplementations, multispectral sensor device 1005 may receiveinformation from and/or transmit information to another device inenvironment 1000, such as heartbeat cycle data device 1010.

Heartbeat cycle data device 1010 includes a device capable of performingone or more operations associated with baseline correcting a heartbeatprofile, as described herein. For example, heartbeat cycle data device1010 may include an application specific integrated circuit (ASIC), anintegrated circuit, a server, a group of servers, and/or the like,and/or another type of communication and/or computing device. In someimplementations, heartbeat cycle data device 1010 may be integrated withmultispectral sensor device 1005 (e.g., such that multispectral sensordevice 1005 and heartbeat cycle data device 1010 are on the same chip,in the same package, in the same housing, and/or the like).Alternatively, in some implementations, heartbeat cycle data device 1010may be separate from multispectral sensor device 1005. In someimplementations, heartbeat cycle data device 1010 may receiveinformation from and/or transmit information to another device inenvironment 1000, such as multispectral sensor device 1005.

Network 1015 includes one or more wired and/or wireless networks. Forexample, network 1015 may include a wired network (e.g., whenmultispectral sensor device 1005 and heartbeat cycle data device 1010are included in same package and/or a same chip). As another example,network 1015 may include a cellular network (e.g., a long-term evolution(LTE) network, a code division multiple access (CDMA) network, a 3Gnetwork, a 4G network, a 5G network, another type of next generationnetwork, etc.), a public land mobile network (PLMN), a local areanetwork (LAN), a wide area network (WAN), a metropolitan area network(MAN), a telephone network (e.g., the Public Switched Telephone Network(PSTN)), a private network, an ad hoc network, an intranet, theInternet, a fiber optic-based network, a cloud computing network, or thelike, and/or a combination of these or other types of networks.

The number and arrangement of devices and networks shown in FIG. 10 areprovided as an example. In practice, there may be additional devicesand/or networks, fewer devices and/or networks, different devices and/ornetworks, or differently arranged devices and/or networks than thoseshown in FIG. 10 . Furthermore, two or more devices shown in FIG. 10 maybe implemented within a single device, or a single device shown in FIG.10 may be implemented as multiple, distributed devices. Additionally, oralternatively, a set of devices (e.g., one or more devices) ofenvironment 1000 may perform one or more functions described as beingperformed by another set of devices of environment 1000.

FIG. 11 is a diagram of example components of a device 1100. Device 1100may correspond to multispectral sensor device 1005 and/or heartbeatcycle data device 1010. In some implementations, multispectral sensordevice 1005 and/or heartbeat cycle data device 1010 may include one ormore devices 1100 and/or one or more components of device 1100. As shownin FIG. 11 , device 1100 may include a bus 1110, a processor 1120, amemory 1130, a storage component 1140, an input component 1150, anoutput component 1160, and a communication interface 1170.

Bus 1110 includes a component that permits communication among multiplecomponents of device 1100. Processor 1120 is implemented in hardware,firmware, and/or a combination of hardware and software. Processor 1120is a central processing unit (CPU), a graphics processing unit (GPU), anaccelerated processing unit (APU), a microprocessor, a microcontroller,a digital signal processor (DSP), a field-programmable gate array(FPGA), an application-specific integrated circuit (ASIC), or anothertype of processing component. In some implementations, processor 1120includes one or more processors capable of being programmed to perform afunction. Memory 1130 includes a random access memory (RANI), a readonly memory (ROM), and/or another type of dynamic or static storagedevice (e.g., a flash memory, a magnetic memory, and/or an opticalmemory) that stores information and/or instructions for use by processor1120.

Storage component 1140 stores information and/or software related to theoperation and use of device 1100. For example, storage component 1140may include a hard disk (e.g., a magnetic disk, an optical disk, and/ora magneto-optic disk), a solid state drive (SSD), a compact disc (CD), adigital versatile disc (DVD), a floppy disk, a cartridge, a magnetictape, and/or another type of non-transitory computer-readable medium,along with a corresponding drive.

Input component 1150 includes a component that permits device 1100 toreceive information, such as via user input (e.g., a touch screendisplay, a keyboard, a keypad, a mouse, a button, a switch, and/or amicrophone). Additionally, or alternatively, input component 1150 mayinclude a component for determining location (e.g., a global positioningsystem (GPS) component) and/or a sensor (e.g., an accelerometer, agyroscope, an actuator, another type of positional or environmentalsensor, and/or the like). Output component 1160 includes a componentthat provides output information from device 1100 (via, e.g., a display,a speaker, a haptic feedback component, an audio or visual indicator,and/or the like).

Communication interface 1170 includes a transceiver-like component(e.g., a transceiver, a separate receiver, a separate transmitter,and/or the like) that enables device 1100 to communicate with otherdevices, such as via a wired connection, a wireless connection, or acombination of wired and wireless connections. Communication interface1170 may permit device 1100 to receive information from another deviceand/or provide information to another device. For example, communicationinterface 1170 may include an Ethernet interface, an optical interface,a coaxial interface, an infrared interface, a radio frequency (RF)interface, a universal serial bus (USB) interface, a Wi-Fi interface, acellular network interface, and/or the like.

Device 1100 may perform one or more processes described herein. Device1100 may perform these processes based on processor 1120 executingsoftware instructions stored by a non-transitory computer-readablemedium, such as memory 1130 and/or storage component 1140. As usedherein, the term “computer-readable medium” refers to a non-transitorymemory device. A memory device includes memory space within a singlephysical storage device or memory space spread across multiple physicalstorage devices.

Software instructions may be read into memory 1130 and/or storagecomponent 1140 from another computer-readable medium or from anotherdevice via communication interface 1170. When executed, softwareinstructions stored in memory 1130 and/or storage component 1140 maycause processor 1120 to perform one or more processes described herein.Additionally, or alternatively, hardware circuitry may be used in placeof or in combination with software instructions to perform one or moreprocesses described herein. Thus, implementations described herein arenot limited to any specific combination of hardware circuitry andsoftware.

The number and arrangement of components shown in FIG. 11 are providedas an example. In practice, device 1100 may include additionalcomponents, fewer components, different components, or differentlyarranged components than those shown in FIG. 11 . Additionally, oralternatively, a set of components (e.g., one or more components) ofdevice 1100 may perform one or more functions described as beingperformed by another set of components of device 1100.

FIG. 12 is a flow chart of an example process 1200 for generating abaseline corrected heartbeat profile, as described herein. In someimplementations, one or more process blocks of FIG. 12 may be performedby a heartbeat cycle data device (e.g., heartbeat cycle data device1010). In some implementations, one or more process blocks of FIG. 12may be performed by another device or a group of devices separate fromor including the heartbeat cycle data device, such as a multispectralsensor device (e.g., multispectral sensor device 1005), and/or the like.

As shown in FIG. 12 , process 1200 may include determining end-of-phaseinformation for a plurality of wavelength channels of PPG data (block1210). For example, the heartbeat cycle data device (e.g., usingprocessor 320, memory 330, storage component 340, input component 350,output component 360, communication interface 370 and/or the like) maydetermine end-of-phase information for a plurality of wavelengthchannels of PPG data, as described above.

As further shown in FIG. 12 , process 1200 may include calculating a setof baseline correction points for each wavelength channel of theplurality of wavelength channels (block 1220). For example, theheartbeat cycle data device (e.g., using processor 320, memory 330,storage component 340, input component 350, output component 360,communication interface 370 and/or the like) may calculate a set ofbaseline correction points for each wavelength channel of the pluralityof wavelength channels, as described above. In some implementations, aset of baseline correction points is calculated based on end-of-phaseinformation for a wavelength channel of the plurality of wavelengthchannels and PPG data associated with the wavelength channel.

As further shown in FIG. 12 , process 1200 may include performing abaseline correction for each wavelength channel of the plurality ofwavelength channels (block 1230). For example, the heartbeat cycle datadevice (e.g., using processor 320, memory 330, storage component 340,input component 350, output component 360, communication interface 370and/or the like) may perform a baseline correction for each wavelengthchannel of the plurality of wavelength channels, as described above. Insome implementations, a baseline correction is performed for thewavelength channel based on the set of baseline correction pointsassociated with the wavelength channel and the PPG data associated withthe wavelength channel.

As further shown in FIG. 12 , process 1200 may include generating abaseline corrected heartbeat profile using a principal componentanalysis of a result of baseline correcting each wavelength channel ofthe plurality of wavelength channels (block 1240). For example, theheartbeat cycle data device (e.g., using processor 320, memory 330,storage component 340, input component 350, output component 360,communication interface 370 and/or the like) may generate a baselinecorrected heartbeat profile using a principal component analysis of aresult of baseline correcting each wavelength channel of the pluralityof wavelength channels, as described above.

Process 1200 may include additional implementations, such as any singleimplementation or any combination of implementations described belowand/or in connection with one or more other processes describedelsewhere herein.

In some implementations, process 1200 includes calculating a set ofbaseline correction points for the baseline corrected heartbeat profile,and performing, using the set of baseline correction points for thebaseline corrected heartbeat profile, a baseline correction for thebaseline corrected heartbeat profile.

In some implementations, the end-of-phase information includesend-of-negative-phase information, and the set of baseline correctionpoints for each wavelength channel is a set of trough points for eachwavelength channel.

In some implementations, the end-of-phase information includesend-of-positive-phase information, and the set of baseline correctionpoints for each wavelength channel is a set of peak points for eachwavelength channel.

In some implementations, the end-of-phase information includesend-of-positive-phase information for the plurality of wavelengthchannels and end-of-negative-phase information for the plurality ofwavelength channels, and the set of baseline correction points for eachwavelength channel is a set of centerline points for each wavelengthchannel. Here, a set of centerline points for a wavelength channel ofthe plurality of wavelength channels is calculated based on a set oftrough points associated with the wavelength channel and a set of peakpoints associated with the wavelength channel.

In some implementations, a set of centerline points for a wavelengthchannel of the plurality of wavelength channels is a set of exactcrossing points.

In some implementations, the set of centerline points for the wavelengthchannel is calculated based on removing all negative-to-positivecrossings between a peak point, of the set of peak points, and asubsequent trough point of the set of trough points, and removing allbut a last negative-to-positive crossing between a trough point, of theset of trough points, and a subsequent peak point of the set of peakpoints.

In some implementations, process 1200 includes identifying a heartbeatcycle as a heartbeat cycle outlier based on baseline correcting eachwavelength channel of the plurality of wavelength channels, and removingthe heartbeat cycle outlier prior to generating the baseline correctedheartbeat profile using the principal component analysis.

In some implementations, the heartbeat cycle is identified as aheartbeat cycle outlier based on determining that a period of theheartbeat cycle differs from a popular heartbeat cycle period by anamount that satisfies a threshold.

In some implementations, process 1200 includes normalizing the result ofbaseline correcting each wavelength channel of the plurality ofwavelength channels prior to generating the baseline corrected heartbeatprofile using the principal component analysis.

Although FIG. 12 shows example blocks of process 1200, in someimplementations, process 1200 may include additional blocks, fewerblocks, different blocks, or differently arranged blocks than thosedepicted in FIG. 12 . Additionally, or alternatively, two or more of theblocks of process 1200 may be performed in parallel.

Some implementations described herein provide a device (e.g., heartbeatcycle data device 1010, multispectral sensor device 1005, and/or thelike) capable of generating a baseline corrected heartbeat profile. Asdescribed above, the baseline corrected heartbeat profile is a heartbeatprofile for which sloping baselines and/or baseline shifts have been atleast partially corrected (e.g., so as to reduce or eliminate an impactof the sloping baselines and/or baseline shifts on the heartbeatprofile). In some implementations, the baseline corrected heartbeatprofile can be used in association with performing a biometricmonitoring action, such as vital sign monitoring (e.g., instantaneousheart rate determination, blood pressure determination, and/or thelike), or another type of biometric determination and/or monitoring(e.g., blood oxygenation determination, augmentation indexdetermination, hydration determination, and/or the like) with improvedaccuracy and/or reliability, as described above.

The foregoing disclosure provides illustration and description, but isnot intended to be exhaustive or to limit the implementations to theprecise forms disclosed. Modifications and variations may be made inlight of the above disclosure or may be acquired from practice of theimplementations.

As used herein, the term “component” is intended to be broadly construedas hardware, firmware, and/or a combination of hardware and software.

Some implementations are described herein in connection with thresholds.As used herein, satisfying a threshold may, depending on the context,refer to a value being greater than the threshold, more than thethreshold, higher than the threshold, greater than or equal to thethreshold, less than the threshold, fewer than the threshold, lower thanthe threshold, less than or equal to the threshold, equal to thethreshold, or the like.

It will be apparent that systems and/or methods described herein may beimplemented in different forms of hardware, firmware, or a combinationof hardware and software. The actual specialized control hardware orsoftware code used to implement these systems and/or methods is notlimiting of the implementations. Thus, the operation and behavior of thesystems and/or methods are described herein without reference tospecific software code—it being understood that software and hardwarecan be designed to implement the systems and/or methods based on thedescription herein.

Even though particular combinations of features are recited in theclaims and/or disclosed in the specification, these combinations are notintended to limit the disclosure of various implementations. In fact,many of these features may be combined in ways not specifically recitedin the claims and/or disclosed in the specification. Although eachdependent claim listed below may directly depend on only one claim, thedisclosure of various implementations includes each dependent claim incombination with every other claim in the claim set.

No element, act, or instruction used herein should be construed ascritical or essential unless explicitly described as such. Also, as usedherein, the articles “a” and “an” are intended to include one or moreitems, and may be used interchangeably with “one or more.” Further, asused herein, the article “the” is intended to include one or more itemsreferenced in connection with the article “the” and may be usedinterchangeably with “the one or more.” Furthermore, as used herein, theterm “set” is intended to include one or more items (e.g., relateditems, unrelated items, a combination of related and unrelated items,etc.), and may be used interchangeably with “one or more.” Where onlyone item is intended, the phrase “only one” or similar language is used.Also, as used herein, the terms “has,” “have,” “having,” or the like areintended to be open-ended terms. Further, the phrase “based on” isintended to mean “based, at least in part, on” unless explicitly statedotherwise. Also, as used herein, the term “or” is intended to beinclusive when used in a series and may be used interchangeably with“and/or,” unless explicitly stated otherwise (e.g., if used incombination with “either” or “only one of”).

What is claimed is:
 1. A method comprising: identifying, by amultispectral sensor device, photoplethysmography data for a pluralityof wavelength channels; transmitting, by the multispectral sensor deviceand to a different device, photoplethysmography data; and receiving, bythe multispectral sensor device, one or more of: a baseline correctedheartbeat profile that is based on a baseline correction performed for awavelength channel, of the plurality of wavelength channels, using a setof baseline correction points associated with the wavelength channel, orinformation associated with the baseline corrected heartbeat profile. 2.The method of claim 1, wherein the photoplethysmography data includesphotometric response data.
 3. The method of claim 2, wherein thephotometric response data indicates a blood volume beneath a skinsurface at a location of the multispectral sensor device at a timepoint.
 4. The method of claim 1, wherein the plurality of wavelengthchannels comprises 64 channels.
 5. The method of claim 1, wherein themultispectral sensor device is configured to be worn on a wrist.
 6. Themethod of claim 1, wherein the multispectral sensor device and thedifferent device are integrated within a same package or a same housing.7. The method of claim 1, wherein the multispectral sensor device islocated remotely from the different device.
 8. The method of claim 1,wherein identifying the photoplethysmography data comprises: obtainingthe photoplethysmography data, and wherein the photoplethysmography datais transmitted by the multispectral sensor device and to the differentdevice as the multispectral sensor device obtains thephotoplethysmography data.
 9. The method of claim 1, whereintransmitting the photoplethysmography data comprises: transmitting thephotoplethysmography data based on one or more of a periodic basis or arequest from the different device.
 10. The method of claim 1, whereinthe information associated with the baseline corrected heartbeat profilecomprises an instantaneous heart rate that is based on the baselinecorrected heartbeat profile.
 11. The method of claim 10, furthercomprising: providing, for display via a display screen of themultispectral sensor device, information that identifies theinstantaneous heart rate.
 12. A multispectral sensor device, comprising:one or more memories; and one or more processors, coupled to the one ormore memories, configured to: provide photoplethysmography data for aplurality of wavelength channels; and identify, based on providing thephotoplethysmography data, one or more of: a baseline correctedheartbeat profile that is based on a baseline correction performed for awavelength channel, of the plurality of wavelength channels, using a setof baseline correction points associated with the wavelength channel, orinformation associated with the baseline corrected heartbeat profile.13. The multispectral sensor device of claim 12, wherein thephotoplethysmography data includes photometric response data thatindicates a blood volume beneath a skin surface at a location of themultispectral sensor device at a time point.
 14. The multispectralsensor device of claim 12, wherein the plurality of wavelength channelscomprises 64 channels.
 15. The multispectral sensor device of claim 12,wherein the one or more processors, to provide the photoplethysmographydata, are configured to: provide, to a heartbeat cycle data device, themultispectral sensor device as the one or more processors obtain thephotoplethysmography data.
 16. The multispectral sensor device of claim12, wherein the information associated with the baseline correctedheartbeat profile comprises an instantaneous heart rate that is based onthe baseline corrected heartbeat profile.
 17. The multispectral sensordevice of claim 16, wherein the one or more processors are furtherconfigured to: provide, for display via a display screen of themultispectral sensor device, information that identifies theinstantaneous heart rate.
 18. A non-transitory computer-readable mediumstoring a set of instructions, the set of instructions comprising: oneor more instructions that, when executed by one or more processors of amultispectral sensor device, cause the multispectral sensor device to:transmit, to a different device, photoplethysmography data for aplurality of wavelength channels; and receive one or more of: a baselinecorrected heartbeat profile that is based on a baseline correctionperformed for a wavelength channel of the plurality of wavelengthchannels, or information associated with the baseline correctedheartbeat profile.
 19. The non-transitory computer-readable medium ofclaim 18, wherein the photoplethysmography data includes photometricresponse data that indicates a blood volume beneath a skin surface at alocation of the multispectral sensor device at a time point.
 20. Thenon-transitory computer-readable medium of claim 18, wherein the one ormore instructions, that cause the multispectral sensor device totransmit the photoplethysmography data, cause the multispectral sensordevice to: transmit the photoplethysmography data based on a requestfrom the different device.